Tsuji et al. BMC Public Health (2018) 18:917
https://doi.org/10.1186/s12889-018-5860-4

RESEARCH ARTICLE

Open Access

Association between education andtelevision viewing among older working
and retired people: a comparative study ofFinland and Japan
Taishi Tsuji1* , Airi Amemiya2, Kokoro Shirai3, Sari Stenholm4, Jaana Pentti4, Tuula Oksanen5, Jussi Vahtera4†
and Katsunori Kondo1,6†

Abstract
Background: Educational attainment is associated with physical activity among older people. However, little is
known about its association with sedentary lifestyle in European as well as Asian nations. This study aims to
examine the associations between educational attainment and daily television viewing as an indicator of asedentary lifestyle among older working and retired people in Finland and Japan.
Methods: We used cross-sectional harmonized data from two cohorts, the Finnish Public Sector study (n = 10,744)
and the Japan Gerontological Evaluation Study (n = 2493), evaluating individuals aged 65–75 years old. We definedhigh-duration television viewing as ≥4 h per day. Poisson regression was used to examine the association between
educational attainment and high-duration television viewing, stratified by the current working status. Models were
adjusted for age, sex, household size, smoking, alcohol, body mass index, chronic diseases, mental disorders, andphysical activity.
Results: Of the participants, 27% in Finland and 30% in Japan reported high-duration television viewing. Compared witha low education (≤9 years), Finnish and Japanese retirees with a high education (≥13 years) had less high-duration
television viewing [prevalence ratio, PR 0.68 (95% confidence interval 0.63–0.73) and 0.66 (0.55–0.79), respectively]. The
corresponding PRs for Finnish and Japanese retirees with intermediate education were also lowered [0.89 (0.83–0.95) and
0.79 (0.68–0.91), respectively]. Among older people still at work, educational attainment was associated with high-duration
television viewing among the Japanese but not among the Finnish.
Conclusion: A similar association between educational attainment and high-duration television viewing in Finland andJapan particularly after retirement suggests a robust and consistent impact of educational attainment on a sedentary
lifestyle after retirements.
Keywords: Television watching, Sedentariness, Elderly, Work status, Retirement* Correspondence: tsuji.t@chiba-u.jp†
Jussi Vahtera and Katsunori Kondo contributed equally to this work.
1
Center for Preventive Medical Sciences, Chiba University, 1-8-1 Inohana,
Chuo Ward, Chiba City, Chiba, Japan
Full list of author information is available at the end of the article© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Tsuji et al. BMC Public Health (2018) 18:917

BackgroundLonger duration of television (TV) viewing, a correlate ofa sedentary lifestyle, is associated with an increased risk ofadverse health outcomes, such as obesity [1–3], diabetes[3, 4], cardiovascular disease [5, 6], cancer [7, 8], and mortality [6, 9]. The potential mechanisms for the adverse relationship between TV viewing and health outcomes
include reduced energy expenditure compared with othersedentary activities, such as reading and driving a car, andan increased food and total energy intake while viewing
TV [3]. Compared with younger or middle-aged people,
the duration of TV viewing tends to increase with age inolder people, particularly after retirement [10]. The daily
TV viewing duration has been found to be approximately
50 min longer for people aged 65–74 years compared withthose aged 55–64 years and was approximately 2 h longer
for unemployed people compared with full-time workersof this age [11]. This further suggests that this behavioral
change poses an additional threat to health of older
people. Therefore, high-duration TV viewing could be
used as a screening tool to identify susceptible groups fortimely interventions.
Several studies have shown that older people with ahigh socioeconomic status (SES) have a higher level ofleisure-time physical activity (PA) and exercise morethan the older people with a lower SES [12, 13]. To
measure the SES of older people, educational attainment, which is normally fixed earlier in life than occupational class or income, is often regarded as a first-choiceindicator because problems of reverse causation aremuch less serious [14, 15]. Murakami and colleagues reported that older individuals who have a higher educational attainment are more likely to have higher levels of
PA [12]. A sedentary lifestyle, however, is not exclusivefrom leisure-time PA and may have adverse effects on
health outcomes independently from leisure-time PA [3,16]. Therefore, the determinants of PA and sedentary
lifestyle are not necessarily the same. Although someprevious studies have reported that a low SES may havean adverse effect on a sedentary lifestyle among youth[17] and adults (partially including older people) [18–20], there is little evidence of the social determinants ofa sedentary lifestyle focusing on older people irrespectiveof nationality or cultural background [21, 22]. Therefore,
this study aimed to examine the association between
educational attainment and sedentary lifestyle evaluatedby the high duration of TV viewing among older working and retired people. Furthermore, we investigated theassociation in both Finland, one of the nations with thehighest level of welfare, and Japan, the nation with theworld’s highest proportion of older people, to clarify
whether a universal relationship exists between two nations’ older populations with different races and cultural
backgrounds.

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Methods
SampleWe collected data from surveys conducted among older
people in Finland and Japan. The Finnish data were derived from the Finnish Public Sector (FPS) cohort study.
FPS study participants were employees representing awide range of occupations working in 10 towns and six
hospital districts. The data used in this study was restricted to participants aged 65–75 who responded to the2013 survey inquiring information on duration of TV
viewing [n = 10,744, response rate = 65% (24,679/38,230)].
The Japanese data were obtained from the Japan Gerontological Evaluation Study (JAGES), a population-based,cross-sectional study of individuals aged 65 years or older
without disability from 31 municipalities, which was conducted between August 2010 and January 2012 (n =112,123; response rate = 66.3%) [23]. The data used in thepresent study were from a sub-sample of the JAGES participants residing in the cities of Kashiwa, Nagoya, andKobe, of which one-fifth provided information on the duration of TV viewing (n = 5360). Participants aged 76 years
or older (n = 2037) were excluded to harmonize with the
FPS samples’ age range. In addition, we excluded 556 participants whose status of TV viewing, educational attainment, or current working status were unknown, and 274
participants never had a job. The studies included a totalof 2493 (1336 men and 1157 women) participants fromJapan and 10,744 (2199 men and 8545 women) participants from Finland.
Measurement of the duration of TV viewing

In the FPS study, the duration of daily TV viewing wasassessed with the following question: “For how many
hours do you sit while watching TV/video every day?” In
the JAGES, the duration was assessed with the following
question: “How much television (including videos) doyou watch in a day on average?” Response options were
< 1 h, 1–2 h, 2–3 h, 3–4 h, and ≥ 4 h in both questions.
We categorized ≥4 h into “high-duration” of TV viewing
on the basis that the threshold elevated the risk of
all-cause and cardiovascular disease mortality [24].
Measurement of educational attainment

Educational attainment was categorized into three levels: (i)≤9 years, i.e., comprehensive school (Finland) and juniorhigh school (Japan); (ii) 10–12 years, i.e., post-compulsory
secondary general academic and vocational education(Finland) and high school and technical college (Japan);and (iii) ≥13 years, i.e., university degree.
Current working status

In the FPS study, a survey response to a question “What isyour current working status?” was used. Participants who
answered “working full-time” or “part-time” were classified

Tsuji et al. BMC Public Health (2018) 18:917

as workers (n = 699), and those who answered “retired” (n = 10,010) or “not working from other causes”(n = 35) were classified as retired. In the JAGES, the participants were asked “What is your current working status?” Those who answered “having a paid job” wereclassified as workers (n = 739), and those who answered“retired” were classified as retired (n = 1754). Those who
answered “never had a job” were excluded from the analysis (n = 274).
Covariates

Other covariates were age (continuous), sex, household
size (1, 2, or ≥ 3 individuals), smoking (never, former, or
current smoker), alcohol consumption (non-drinker orcurrent drinker), chronic diseases (having one or moreof the following diseases: cancer, cardiovascular diseases,
stroke, and diabetes mellitus), mental disorders (a scoreof ≥4 in the 12-Item General Health Questionnaire [25]in the FPS study and a score of ≥11 in the Geriatric Depression Scale [26, 27] in the JAGES), and moderate/vigorous PA (< 1 day per week or ≥ 1 day per week). In the
FPS study, the participants were asked about their average weekly hours of leisure-time PA (including commuting) within the previous year spent walking, brisk
walking, jogging, and running, or their equivalent activities. The participants were classified based on whether
they performed brisk walking (and equivalent) or ahigher intensity of PA for 1 h per week or longer. In the
JAGES, the participants were asked about their frequency of low-, middle-, and high-intensity PA and wereclassified based on whether middle- and/or high-intensity PA was practiced at least once a week or less thanonce a week. Body mass index (BMI) was calculated as
the self-reported weight divided by the square of theself-reported height and then categorized as < 18.5,
18.5–24.9, 25–29.9, and ≥ 30. Missing values weretreated as dummy variables.
Statistical analysis

A Poisson regression analysis stratified by the current
working status was performed to examine the effect ofeducational attainment on the duration of TV viewing.
Model 1 was adjusted for age and sex. Model 2 was adjusted for smoking, alcohol consumption, BMI, household
size, chronic diseases, and mental disorders. Model 3 wasfurther adjusted for moderate/vigorous PA. Prevalence ratios (PRs) and their 95% confidence intervals (95% CIs)
were calculated. We also conducted sensitivity analyses
with outcomes set to cut points of ≥3 h and ≥ 2 h per day
for high-duration TV viewing. Statistical analysis was performed using the SAS statistical software, version 9.1.3(SAS Institute, Inc., Cary, North Carolina) and IBM SPSS
Statistics 22 (IBM Corp. Armonk, New York).

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Results
Table 1 shows the descriptive cohort-specific data of theparticipants combined and by their working status. In theJapanese study, 46% were women compared with 80% in
the Finnish study. The proportion of moderate/vigorous
PA one day per week or more was higher in Finland thanin Japan. The prevalence of high-duration TV viewing was
somewhat lower in Finland (27%) than in Japan (30%). Retired participants had a high-duration TV viewing more
frequently than those still working in both countries(Finland: 28% vs. 16%; Japan: 34% vs. 19%).
Table 2 shows the association between educational attainment and high-duration TV viewing by the working
status for each cohort. In both cohorts, irrespective of
the working status, the level of education was inversely
associated with unadjusted values for high-duration TV
viewing. After adjusting for all covariates, the associations attenuated but remained significant with one exception, the FPS participants were still working. The
fully adjusted prevalence compared with those with alow education was 0.68-fold (95% CI: 0.63–0.73) for highand 0.89-fold (0.83–0.95) for intermediate education
among retired FPS cohort members. The correspondingPRs for retired JAGES cohort members were 0.66 (0.55–0.79) and 0.79 (0.68–0.91), respectively. Among working
JAGES cohort members with high education comparedwith low education, the prevalence of high-duration TV
time was almost the same than that among the retirees,in which the fully adjusted prevalence was 0.63-fold(0.42–0.93). An additional table presents the results ofthe sensitivity analyses with outcomes set to TV viewing
durations of ≥3 h and ≥ 2 h per day (see Additional file 1).
A similar, albeit marginally weaker tendency of the relationship was observed for these lower cut points forhigh-duration TV viewing.
Discussion
The present study found that educational attainment issimilarly associated with the duration of TV viewing
among older people after retirement in Finland andJapan, which suggests the robust and consistent positive
impact of higher educational attainment on avoiding asedentary lifestyle among those who have retired fromtheir job. This association was found to exist independently of moderate/vigorous PA. Furthermore, the association was also significant among the older current
workers in Japan; however, it was not significant amongthat subgroup in Finland.
Our results regarding retired populations are in linewith those of earlier reports indicating a significant association between high education and habitual exercise inolder people [12]. Even if the assumed confounders andmediators were adjusted in the present study, the strengthof the association between educational attainment andTsuji et al. BMC Public Health (2018) 18:917

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Table 1 Descriptive data of participants for each cohort and each current working status
Finland

Japan

Total

Working

RetiredTotal

Working

Retired(n = 10,744)(n = 699)(n = 10,045)(n = 2,493)(n = 739)(n = 1,754)<2 hours

1,309

12.2%

156

22.3%

1,153

11.5%

455

18.3%

183

24.8%

272

15.5%

2-<3 hours

3,148

29.3%

261

37.3%

2,887

28.7%

627

25.2%

221

29.9%

406

23.1%

3-<4 hours

3,392

31.6%

173

24.7%

3,219

32.0%

672

27.0%

198

26.8%

474

27.0%

≥4 hours

2,895

26.9%

109

15.6%

2,786

27.7%

739

29.6%

137

18.5%

602

34.3%

Low: ≤9 years

1,958

18.2%

65

9.3%

1,893

18.8%

683

27.4%

217

29.4%

466

26.6%

Middle: 10–12 years

3,362

31.3%

180

25.8%

3,182

31.7%

1,031

41.4%

276

37.3%

755

43.0%

High: ≥13 years

5,424

50.5%

454

64.9%

4,970

49.5%

779

31.2%

246

33.3%

533

30.4%

68.5

2.6

67.4

2.3

68.5

2.7

70.1

2.8

69.5

2.7

70.4

2.8

Men

2,199

20.5%

197

28.2%

2,002

19.9%

1,336

53.6%

457

61.8%

879

50.1%

Women

8,545

79.5%

502

71.8%

8,043

80.1%

1,157

46.4%

282

38.2%

875

49.9%

1 person

3,590

33.4%

278

39.8%

3,312

33.0%

371

14.9%

102

13.8%

269

15.3%

2 people

6,385

59.4%

372

53.2%

6,013

59.9%

1,260

50.5%

345

46.7%

915

52.2%

≥3 people

244

2.3%

27

3.9%

217

2.2%

763

30.6%

263

35.6%

500

28.5%

Missing

525

4.9%

22

3.1%

503

5.0%

99

4.0%

29

3.9%

70

4.0%

Daily TV viewing (n, %)Education (n, %)Age (mean, SD)
Years
Sex (n, %)Household size (n, %)Body mass index (n, %)<18.5 kg/m2

99

0.9%

3

0.4%

96

1.0%

149

6.0%

36

4.9%

113

6.4%

2

18.5–24.9 kg/m

4,071

37.9%

272

38.9%

3,799

37.8%

1,805

72.4%

534

72.3%

1,271

72.5%

25.0–29.9 kg/m2

4,091

38.1%

291

41.6%

3,800

37.8%

454

18.2%

148

20.0%

306

17.4%

≥30.0 kg/m

1,949

18.1%

109

15.6%

1,840

18.3%

44

1.8%

14

1.9%

30

1.7%

Missing

534

5.0%

24

3.4%

510

5.1%

41

1.6%

7

0.9%

34

1.9%

Never

7,986

74.3%

510

73.0%

7,476

74.4%

1,155

46.3%

328

44.4%

827

47.1%

Former

2,022

18.8%

133

19.0%

1,889

18.8%

802

32.2%

251

34.0%

551

31.4%

Current

694

6.5%

55

7.9%

639

6.4%

338

13.6%

109

14.7%

229

13.1%

Missing

42

0.4%

1

0.1%

41

0.4%

198

7.9%

51

6.9%

147

8.4%

Non-drinker

2,265

21.1%

128

18.3%

2,137

21.3%

1,195

47.9%

316

42.8%

879

50.1%

Drinker

8,452

78.7%

569

81.4%

7,883

78.5%

1,129

45.3%

380

51.4%

749

42.7%

Missing

27

0.3%

2

0.3%

25

0.2%

169

6.8%

43

5.8%

126

7.2%

2

Smoking (n, %)Alcohol (n, %)Current chronic disease (n, %)
No

7,397

68.8%

523

74.8%

6,874

68.4%

1,215

48.7%

363

49.1%

852

48.6%

Yes

3,266

30.4%

174

24.9%

3,092

30.8%

590

23.7%

148

20.0%

442

25.2%

Missing

81

0.8%

2

0.3%

79

0.8%

688

27.6%

228

30.9%

460

26.2%

Tsuji et al. BMC Public Health (2018) 18:917

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Table 1 Descriptive data of participants for each cohort and each current working status (Continued)
Finland

Japan

Total

Working

RetiredTotal

Working

Retired(n = 10,744)(n = 699)(n = 10,045)(n = 2,493)(n = 739)(n = 1,754)

Common mental disorders (n, %)
No

9,451

88.0%

656

93.8%

8,795

87.6%

1,966

78.9%

594

80.4%

1,372

78.2%

Yes

1,203

11.2%

39

5.6%

1,164

11.6%

81

3.2%

18

2.4%

63

3.6%

Missing

90

0.8%

4

0.6%

86

0.9%

446

17.9%

127

17.2%

319

18.2%

Moderate/vigorous physical activity (n, %)<1 day/week

3,174

29.5%

173

24.7%

3,001

29.9%

1,031

41.4%

365

49.4%

666

38.0%

≥1 day/week

7,484

69.7%

520

74.4%

6,964

69.3%

1,310

52.5%

338

45.7%

972

55.4%

Missing

86

0.8%

6

0.9%

80

0.8%

152

6.1%

36

4.9%

116

6.6%

a low education and smaller pension. Thus, a high durationof TV viewing would be among the pathways maintaining
inequalities in health among older people.
Among older people still working, educational attainment was associated with high-duration TV viewing onlyin Japan, whereas among retirees, a similar inverse association was observed in both countries. Thus, cultural
backgrounds such as those between Finland and Japan,
may lead to different pathways through which education

duration of daily TV viewing hardly changed among thoseolder people who no longer work. Income, factual knowledge, enduring cognitive or emotional skills, and social
network are regarded as mechanisms that link education
to health behaviors and health outcomes [28]. Anotherpossibility is that individuals with a higher education have agood pension which enables them to engage in various
leisure-time activities, which require expenditure of money
rather than TV viewing, an option less likely for those with

Table 2 Association between educational attainment and high-duration of TV viewing for each cohort and each current working
status
Crude model

Model 1PR

95% CIPR

95% CI

Model 2PR

95% CI

Model 3PR

95% CI

Low: ≤9 years

1.00

ref.

1.00

ref.

1.00

ref.

1.00

ref.

Middle: 10–12 years

0.87(0.51 – 1.47)

0.90(0.52 – 1.54)

0.93(0.55 – 1.55)

0.96(0.56 – 1.62)

High: ≥13 years

0.55(0.33 – 0.92)

0.59(0.36 – 0.98)

0.77(0.47 – 1.26)

0.78(0.47 – 1.29)

Low: ≤9 years

1.00

ref.

1.00

ref.

1.00

ref.

1.00

ref.

Middle: 10–12 years

0.82(0.76 – 0.88)

0.83(0.77 – 0.90)

0.89(0.82 – 0.95)

0.89(0.83 – 0.95)

High: ≥13 years

0.54(0.50 – 0.58)

0.54(0.50 – 0.59)

0.67(0.62 – 0.72)

0.68(0.63 – 0.73)

1.00

ref.

1.00

ref.

1.00

ref.

1.00

ref.

Finland
Working (n = 699)

Retired (n = 10,045)

Japan
Working (n = 739)
Low: ≤9 years
Middle: 10–12 years

0.77(0.54 – 1.09)

0.74(0.53 – 1.05)

0.73(0.51 – 1.03)

0.75(0.53 – 1.06)

High: ≥13 years

0.62(0.42 – 0.92)

0.62(0.42 – 0.92)

0.61(0.41 – 0.91)

0.63(0.42 – 0.93)

1.00

ref.

1.00

ref.

1.00

ref.

1.00

ref.

Retired (n = 1754)
Low: ≤9 years
Middle: 10–12 years

0.76(0.66 – 0.88)

0.75(0.65 – 0.87)

0.77(0.67 – 0.89)

0.79(0.68 – 0.91)

High: ≥13 years

0.63(0.53 – 0.74)

0.61(0.51 – 0.73)

0.64(0.54 – 0.77)

0.66(0.55 – 0.79)

PR: prevalence ratio, CI: confidence interval
Model 1: crude model + age and sex
Model 2: model 1 + household size, smoking, alcohol, body mass index, current chronic disease, and common mental disorders
Model 3: model 2 + moderate/vigorous physical activity

Tsuji et al. BMC Public Health (2018) 18:917

is linked to behavior-related risks when people are still
at work. According to a survey comparing 10 European
countries regarding how one spends time in everyday
life, Finnish people had the longest reading time,
whereas their TV viewing was moderate [29]. Conversely, as observed from the results of this study, theJapanese taste for TV viewing may be stronger than thatof Finnish people. Therefore, in Japan, even older
workers tend to spend their indoor leisure time on TV
viewing, particularly if they have a low educational attainment. Because TV viewing further reduces individuals’ energy expenditure compared with, e.g., reading asfood and total energy intake is increased due to a tendency to eat while watching TV [3], there is a need forpreventive measures to shorten the TV viewing especially among the older people with a low educational attainment in both countries.
A strength of this study is that it is based on harmonizedvariables from two large cohorts of the older people: one
from Finland, a Scandinavian welfare state, and one fromJapan, one of the world’s highest longevity nation. However, this study also has several limitations. First, a sedentary lifestyle was indirectly evaluated by TV viewing time(including videos) based on self-reported questionnaires
in the present studies. Other screen-time behaviors (e.g.,
computer and video games) and overall sitting time were
not considered. Second, the question formats in each cohort differed for potential mediators, particularly moderate/vigorous PA. However, as further adjustment for PA
had little effect on the observed associations, such heterogeneity is an unlikely source of major bias in the comparisons. Third, we used educational attainment as a measureof SES in both studies. A more comprehensive measurement of SES at an old age would also include income andoccupational status, given that educational attainment is adeterminant of future income and occupation [28].
Fourth, because we did not collect compatible variables ofenvironmental factors between two cohorts, we only focused on individual factors. Previous studies have, however, reported that, for example, neighborhood poor
walkability was associated with higher durations of daily
TV viewing in adults [21, 30]. Further investigation considering built environment factors are required. Finally,
the data were cross-sectional. Although the time order between educational attainment and TV-viewing time at an
old age is likely to be correct, the exposure and potential
mediators were measured simultaneously.

Conclusion
Lower educational attainment was associated with highduration TV viewing, which is similar in Finland andJapan, particularly after retirement. This suggests a robust and consistent impact of educational attainment on
a sedentary lifestyle after retirement.

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Additional file
Additional file 1: Table S3. Association between educational attainment
and TV viewing durations (≥3 h and ≥ 2 h per day) for each cohort andeach current working status. The additional table presents the results of thesensitivity analyses with outcomes set to TV viewing durations of ≥3 hand ≥ 2 h per day. (XLSX 16 kb)

Abbreviations
BMI: Body mass index; CI: Confidence interval; FPS: The Finnish Public Sector;
JAGES: the Japan Gerontological Evaluation Study; PA: Physical activity;
PR: Prevalence ratio; SES: Socioeconomic status; TV: Television
Acknowledgements
We would like to thank the study participants.
Availability of data and material
The data underlying this study are from the FPS study and the JAGES andcontain sensitive information. Data for research purposes are available uponrequest. Requests for the FPS and the JAGES data can be made to
kuntasektori@ttl.fi and dataadmin.ml@jages.net, respectively.
Funding
The FPS was supported by the participating organizations. SS was supportedby the Academy of Finland and JP and JV by NordForsk, the Nordic
Programme on Health and Welfare. The JAGES was supported by a grant of
the Strategic Research Foundation Grant-aided Project for Private Universities
from the Ministry of Education, Culture, Sport, Science, and Technology,
Japan (MEXT), 2009–2013, for the Center for Well-being and Society, Nihon
Fukushi University; a Health Labour Sciences Research Grant, Comprehensive
Research on Aging and Health (H22-Choju-Shitei-008, H24-JunkankitouIppan-007, H24-Chikyukibo-Ippan-009, H24-Choju-Wakate-009, H25-KenkiWakate-015, H25-Irryo-Shitei-003 (Fukkou), H26-Choju-Ippan-006, H28-ChoujuIppan-02, H28-Ninchisho-Ippan-002) from the Japanese Ministry of Health,Labour and Welfare; JSPS KAKENHI (22330172, 22390400, 23243070,
23590786, 23790710, 24390469, 24530698, 24653150, 24683018, 25253052,
25870573, 25870881, 22390400, 15K18174, 15KT0007, 15H01972, 16K16595,
17K15822) from the Japan Society for the Promotion of Science; a grant fromthe National Center for Geriatrics and Gerontology (24–17, 24–23); the Research and Development Grants for Longevity Science from AMED; a grantfrom the Japan Foundation for Aging and Health; and also World HealthOrganization Centre for Health Development (WHO Kobe Centre) (WHOAPW 2017/713981). The funding bodies played no role in study design, datacollection and analysis, interpretation of data, and writing of the manuscript.
Authors’ contributions
Conception and writing the article: TT; design: TT, AA, and KS; analysis andinterpretation of the data: TT, SS, and JP; data collection: TO, JV and KK;
critical revision of the article: AA, KS, SS, JP, TO, JV, and KK; principal
investigator for the FPS: JV; and principal investigator for the JAGES: KK. All
authors read and approved the final manuscript.
Competing interest
The authors have no conflict of interest to declare.
Ethics approval and consent to participate
The FPS study was approved by the Ethics Committee of the Helsinki and
Uusimaa Hospital District. Answering to the FPS survey was voluntary andthe completed questionnaire acted as an informed consent. The JAGES wasby the Ethics Committee for Research on Human Subjects at Nihon Fukushi
University, Japan (No. 10–05). JAGES participants were informed thatparticipation in the study was voluntary and that completing and returning
the questionnaire via mail indicated their consent to participate in the study.
Consent for publication
Not applicable.

Tsuji et al. BMC Public Health (2018) 18:917

Page 7 of 7

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Author details
1
Center for Preventive Medical Sciences, Chiba University, 1-8-1 Inohana,
Chuo Ward, Chiba City, Chiba, Japan. 2Department of Health Education and
Health Sociology, School of Public Health, The University of Tokyo, 7-3-1
Hongo, Bunkyo Ward, Tokyo, Japan. 3Department of Public Health, Graduate
School of Medicine, Osaka University, 2-2 Yamadaoka, Suita City, Osaka,
Japan. 4Department of Public Health, University of Turku and Turku
University Hospital, 20014 Turun yliopisto, Turku, Finland. 5Finnish Institute ofOccupational Health, Topeliuksenkatu 41 b (Headquarters), 00250 Helsinki,
Finland. 6Department of Gerontology and Evaluation Study, Center for
Gerontology and Social Science, National Center for Geriatrics andGerontology, 7-430 Morioka-cho, Obu City, Aichi, Japan.

18.

19.

20.

21.

Received: 27 March 2018 Accepted: 17 July 201822.
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